Ceramic 3D grid model shape similarity discrimination method and device

Abstract

The invention discloses a ceramic 3D grid model shape similarity discrimination method and device; the method comprises the following steps: using two sets of ceramic 3D grid models as input, and standardizing the input data; building a set of vertical planes, respectively intersecting each vertical plane with the standardized two sets of ceramic 3D grid models, and arranging the intersection lines obtained by each ceramic 3D grid model in sequence, thus forming a first intersection line sequence PSA and a second intersection line sequence PSB; calculating the difference between the intersection line PSAi and PSBi corresponding to the two intersection line sequences in order, thus forming a corresponding difference sequence SAB; using the difference sequence SAB statistical result as the similarity of the two sets of the ceramic 3D grid models. The method uses the ceramic 3D grid model shape expression characteristics, converts hardly expressed shape characteristics into the intersection line sequence formed by line segments on one hand, and uses the difference statistical result between the intersection lines as the ceramic 3D grid model shape similarity on the other hand.

Description

technical field [0001] The invention relates to the technical fields of computer vision and computer graphics, in particular to a method and device for discriminating similarity of ceramic three-dimensional mesh models. Background technique [0002] The similarity discrimination of ceramic wares is an important problem in the field of ceramic design, and it has a very wide range of applications in the fields of copyright protection and design reuse. Due to the limitations of the shape characteristics of ceramic products, it is difficult to directly evaluate the similarity of similar ceramic products in terms of shape. For example, a ceramic designer designs a porcelain bottle through 3D design software and exports the design result as a 3D mesh model Easy to show. For multiple 3D grid models of porcelain vases, the features of the vessel types contained in them are very similar, such as bottle mouth, bottle belly, bottle bottom, etc. Traditional similarity evaluation method...

AI Technical Summary

Problems solved by technology

For multiple 3D mesh models of porcelain vases, the features of the utensils contained in them are very similar, such as the mouth, belly, bottom, etc., and the traditional similarity evaluation methods cannot judge the similarity of the utensils well.

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